{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Thermal Transport from NEMD\n",
    "## Introduction\n",
    "In this tutorial, we use the NEMD method to study heat transport in graphene at 300 K and zero pressure. Here we consider the ballistic regime. The diffusive regime can be found in the HNEMD example. The spectral decomposition method as described in [[Fan 2019]](https://doi.org/10.1103/PhysRevB.99.064308) is used here."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing Relevant Functions\n",
    "The inputs/outputs for GPUMD are processed using the [Atomic Simulation Environment (ASE)](https://wiki.fysik.dtu.dk/ase/) package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pylab import *\n",
    "from ase.build import graphene_nanoribbon\n",
    "from ase.io import write"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preparing the Inputs\n",
    "We consider a graphene sheet of size of about 25 nm x 43 nm (40400 atoms). The transport is in the $y$ direction. We divide the length in the $y$ direction into 9 groups. Group 0 (a small one) will be fixed. Group 1 (about 9 nm long) will act as a heat source and group 8 (about 9 nm long) will act as a sink. The remaining middle part is evenly divided into a few groups (group 2 to group 7).\n",
    "We use a Tersoff potential [[Tersoff 1989]](https://doi.org/10.1103/PhysRevB.39.5566) parameterized by Lindsay *et al.* [[Lindsay 2010]](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.81.205441).\n",
    "\n",
    "### Generate the  [model.xyz](https://gpumd.org/gpumd/input_files/model_xyz.html) file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Atoms(symbols='C40400', pbc=[True, True, False], cell=[245.95121467478057, 430.26, 3.35])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gnr = graphene_nanoribbon(100, 101, type='armchair', sheet=True, vacuum=3.35/2)\n",
    "gnr.euler_rotate(theta=90)\n",
    "lx, lz, ly = gnr.cell.lengths()\n",
    "gnr.cell = gnr.cell.new((lx, ly, lz))\n",
    "gnr.center()\n",
    "gnr.pbc = [True, True, False]\n",
    "gnr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add Groups for NEMD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "y-direction boundaries: [0, 3.9, 89.55, 132.18, 174.81, 217.43, 260.06, 302.68, 345.31, 430.26]\n"
     ]
    }
   ],
   "source": [
    "split = np.array([ly/100] + [ly/5] + [ly/10]*6)-0.4\n",
    "split = [0] + list(np.cumsum(split)) + [ly]\n",
    "print(\"y-direction boundaries:\", [round(x,2) for x in split])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "group_label = []\n",
    "for i, atom in enumerate(gnr):\n",
    "    y_pos = atom.position[1]\n",
    "    for j in range(len(split)):\n",
    "        if y_pos > split[j] and y_pos < split[j+1]:\n",
    "            group_label.append(j)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "gnr.arrays[\"group\"] = np.array(group_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "group 0: 400 atoms\n",
      "group 1: 8000 atoms\n",
      "group 2: 4000 atoms\n",
      "group 3: 4000 atoms\n",
      "group 4: 4000 atoms\n",
      "group 5: 4000 atoms\n",
      "group 6: 4000 atoms\n",
      "group 7: 4000 atoms\n",
      "group 8: 8000 atoms\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(split)-1):\n",
    "    atom_num = len(gnr[gnr.arrays[\"group\"] == i])\n",
    "    print(f\"group {i}: {atom_num} atoms\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "write(\"model.xyz\", gnr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The `run.in file:\n",
    "The [run.in input file](https://gpumd.org/gpumd/input_files/run_in.html) is given below:<br>\n",
    "```\n",
    "potential    ../../../../potentials/tersoff/Graphene_Lindsay_2010_modified.txt\n",
    "velocity     300\n",
    "\n",
    "ensemble     nvt_ber 300 300 100\n",
    "fix          0\n",
    "time_step    1 \n",
    "dump_thermo  1000        \n",
    "run          100000\n",
    "\n",
    "ensemble     heat_lan 300 100 10 1 8 \n",
    "fix          0\n",
    "compute      0 10 100 temperature\n",
    "compute_shc  2 250 1 1000 400.0 group 0 4\n",
    "run          1000000\n",
    "```\n",
    "\n",
    "The first line uses the [potential](https://gpumd.org/gpumd/input_parameters/potential.html) keyword to define the potential to be used, which is specified in the file [Graphene_Lindsay_2010_modified.txt](https://github.com/brucefan1983/GPUMD/blob/master/potentials/tersoff/Graphene_Lindsay_2010_modified.txt).\n",
    "\n",
    "The second line uses the [velocity](https://gpumd.org/gpumd/input_parameters/velocity.html) keyword and sets the velocities to be initialized with a temperature of 300 K. \n",
    "\n",
    "There are two runs. The first [run](https://gpumd.org/gpumd/input_parameters/run.html) serves as the equilibration stage.\n",
    "\n",
    "  - Here, the NVT [ensemble](https://gpumd.org/gpumd/input_parameters/ensemble.html) (the Berendsen thermostat) is used. The target temperature is 300 K and the coupling constant is 100 time steps for the thermostat. \n",
    "  - The [time_step](https://gpumd.org/gpumd/input_parameters/time_step.html) for integration is 1 fs. \n",
    "  - Atoms in group 0 will be fixed. \n",
    "  - The thermodynamic quantities will be output every 1000 steps. \n",
    "  - There are $10^5$ steps (100 ps) for this run. \n",
    "\n",
    "The second [run](https://gpumd.org/gpumd/input_parameters/run.html) is for production. \n",
    "\n",
    "  - Here, two local Langevin thermostats ([ensemble](https://gpumd.org/gpumd/input_parameters/ensemble.html)) are applied to generate a nonequilibrium heat current. The time parameter in the Langevin thermostats is 0.1 ps (100 time steps). The target temperature of the heat source is $300+10=310$ K and the target temperature of the heat sink is $300-10=290$ K. Atoms in group 1 are in the heat source region and atoms in group 8 are in the heat sink region.\n",
    "  - Atoms in group 0 will be fixed. \n",
    "  - The [compute](https://gpumd.org/gpumd/input_parameters/compute.html) is used to compute the group temperatures and energy transfer rate. Here, grouping method 0 is used, and the relevant data are sampled every 10 time steps and averaged for every 100 data points before written out. \n",
    "  - The line with the [compute_shc](https://gpumd.org/gpumd/input_parameters/compute_shc.html) keyword is used to compute the spectral heat current (SHC). The SHC will be calculated for group <code>4</code> in grouping method <code>0</code>. The relevant data will be sampled every 2 steps and the maximum correlation time is $250 \\times 2 \\times 1~{\\rm fs} = 500~{\\rm fs}$. The transport directions is <code>1</code> ($y$ direction). The number of frequency points is 1000 and the maximum angular frequncy is 400 THz.\n",
    "  - There are $10^6$ steps (1 ns) in the production [run](https://gpumd.org/gpumd/input_parameters/run.html). This is just an example. To get more accurate results, we suggest you use $10^7$ steps (10 ns)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results and Discussion\n",
    "### Computation Time\n",
    "- Using a GeForce RTX 2080 Ti GPU, the NEMD simulation takes about 15 minutes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure Properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "aw = 2\n",
    "fs = 16\n",
    "font = {'size'   : fs}\n",
    "matplotlib.rc('font', **font)\n",
    "matplotlib.rc('axes' , linewidth=aw)\n",
    "\n",
    "def set_fig_properties(ax_list):\n",
    "    tl = 8\n",
    "    tw = 2\n",
    "    tlm = 4\n",
    "    \n",
    "    for ax in ax_list:\n",
    "        ax.tick_params(which='major', length=tl, width=tw)\n",
    "        ax.tick_params(which='minor', length=tlm, width=tw)\n",
    "        ax.tick_params(axis='both', direction='in', right=True, top=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot NEMD Results\n",
    "The [compute.out](https://gpumd.org/gpumd/output_files/compute_out.html) output file is loaded and processed to create the following figure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "compute = np.loadtxt(\"compute.out\")\n",
    "temp = compute[:, :9]\n",
    "ndata = temp.shape[0]\n",
    "Ein = compute[:, 9]\n",
    "Eout = compute[:, 10]\n",
    "temp_ave = np.mean(temp[int(ndata/2)+1:, 1:], axis =0) #unit in K\n",
    "\n",
    "dt = 0.001  # ps \n",
    "Ns = 1000  # Sample interval\n",
    "t = dt*np.arange(1,ndata+1) * Ns/1000  # ns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(figsize=(10,5))\n",
    "subplot(1,2,1)\n",
    "set_fig_properties([gca()])\n",
    "group_idx = range(1,9)\n",
    "plot(group_idx, temp_ave,linewidth=3,marker='o',markersize=10)\n",
    "xlim([1, 8])\n",
    "gca().set_xticks(group_idx)\n",
    "ylim([290, 310])\n",
    "gca().set_yticks(range(290,311,5))\n",
    "xlabel('group index')\n",
    "ylabel('T (K)')\n",
    "title('(a)')\n",
    "\n",
    "subplot(1,2,2)\n",
    "set_fig_properties([gca()])\n",
    "plot(t, Ein/1000, 'C3', linewidth=3)\n",
    "plot(t, Eout/1000, 'C0', linewidth=3, linestyle='--' )\n",
    "xlim([0, 1])\n",
    "gca().set_xticks(linspace(0,1,6))\n",
    "ylim([-10, 10])\n",
    "gca().set_yticks(range(-10,11,5))\n",
    "xlabel('t (ns)')\n",
    "ylabel('Heat (keV)')\n",
    "title('(b)')\n",
    "tight_layout()\n",
    "show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(a)** Temperature profile in the NEMD simulation. **(b)** Energies accumulated in the thermostats."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- The figure above shows the temperature profile and the energies accumulated in the thermostats. The energy of the thermostat coupling to the heat source region is decreasing, because energy is transferred from the thermostat to the atoms in the source region. The energy of the thermostat coupling to the heat sink region is increasing, because energy is transferred from the atoms in the sink region to the thermostat. The absolute values of the slopes of the lines in **(b)** should be the same; otherwise it means energy is not conserved. The absolute slope is the energy transfer rate $Q=dE/dt$.\n",
    "- The thermal conductance in this system can be calculated as\n",
    "$$\n",
    "G = \\frac{Q/S}{\\Delta T}\n",
    "$$\n",
    "where $S$ is the cross-sectional area and $\\Delta T$ is the temperature difference, which is 19 K here (slightly smaller than the target value of 20 K). The calculated thermal conductance is about 10 GW m<sup>-2</sup> K<sup>-1</sup>. This is the classical value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19.046382565130557"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deltaT = temp_ave[0] - temp_ave[-1]  # [K]\n",
    "deltaT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.635182"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q1 = (Ein[int(ndata/2)] - Ein[-1])/(ndata/2)/dt/Ns\n",
    "Q2 = (Eout[-1] - Eout[int(ndata/2)])/(ndata/2)/dt/Ns\n",
    "Q = mean([Q1, Q2])  # [eV/ps]\n",
    "Q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.823666787865204"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l = gnr.cell.lengths()\n",
    "A = l[0]*l[2]/100  # [nm2]\n",
    "G = 160*Q/deltaT/A  # [GW/m2/K]\n",
    "G"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot Spectral Heat Current Results\n",
    "The [shc.out](https://gpumd.org/gpumd/output_files/shc_out.html) output file is loaded and processed to create the following figure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['t', 'Ki', 'Ko', 'omega', 'jwi', 'jwo', 'nu'])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_corr_points, num_omega = 250, 1000\n",
    "\n",
    "labels_corr = ['t', 'Ki', 'Ko']\n",
    "labels_omega = ['omega', 'jwi', 'jwo']\n",
    "\n",
    "num_corr_points_in_run = num_corr_points * 2 - 1\n",
    "coor_array = np.loadtxt(\"shc.out\", max_rows=num_corr_points_in_run)\n",
    "omega_array = np.loadtxt(\"shc.out\", skiprows=num_corr_points_in_run)\n",
    "\n",
    "shc = dict()\n",
    "for label_num, key in enumerate(labels_corr):\n",
    "    shc[key] = coor_array[:, label_num]\n",
    "\n",
    "for label_num, key in enumerate(labels_omega):\n",
    "    shc[key] = omega_array[:, label_num]\n",
    "shc[\"nu\"] = shc[\"omega\"] / (2*np.pi)\n",
    "\n",
    "shc.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "Ly = split[5]-split[4]\n",
    "Lx, Lz = l[0], l[2]\n",
    "V = Lx*Ly*Lz\n",
    "Gc = 1.6e4*(shc['jwi']+shc['jwo'])/V/deltaT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(figsize=(10,5))\n",
    "subplot(1,2,1)\n",
    "set_fig_properties([gca()])\n",
    "plot(shc['t'], (shc['Ki']+shc['Ko'])/Ly, linewidth=2)\n",
    "xlim([-0.5, 0.5])\n",
    "gca().set_xticks([-0.5, 0, 0.5])\n",
    "ylim([-4, 10])\n",
    "gca().set_yticks(range(-4,11,2))\n",
    "ylabel('K (eV/ps)')\n",
    "xlabel('Correlation time (ps)')\n",
    "title('(a)')\n",
    "\n",
    "subplot(1,2,2)\n",
    "set_fig_properties([gca()])\n",
    "plot(shc['nu'], Gc, linewidth=2)\n",
    "xlim([0, 50])\n",
    "gca().set_xticks(range(0,51,10))\n",
    "ylim([0, 0.35])\n",
    "gca().set_yticks(linspace(0,0.35,8))\n",
    "ylabel(r'$G$($\\omega$) (GW/m$^2$/K/THz)')\n",
    "xlabel(r'$\\omega$/2$\\pi$ (THz)')\n",
    "title('(b)')\n",
    "tight_layout()\n",
    "show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(a)** Virial-velocity correlation function. **(b)** Spectral thermal conductance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The figure above shows the virial-velocity correlation function $K(t)$ and the spectral thermal conductance $G(\\omega)$. See [Theoretical formulations](https://gpumd.zheyongfan.org/index.php/Theoretical_formulations) for the definitions of these quantities. Using the spectral thermal conductance, one can perform quantum correction, see [[Li 2019]](https://doi.org/10.1063/1.5132543)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save('../diffusive/Gc.npy', Gc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "- [Fan 2019] Zheyong Fan, Haikuan Dong, Ari Harju, and Tapio Ala-Nissila, [Homogeneous nonequilibrium molecular dynamics method for heat transport and spectral decomposition with many-body potentials](https://doi.org/10.1103/PhysRevB.99.064308), Phys. Rev. B **99**, 064308 (2019).\n",
    "- [Li 2019] Zhen Li, Shiyun Xiong, Charles Sievers, Yue Hu, Zheyong Fan, Ning Wei, Hua Bao, Shunda Chen, Davide Donadio, and Tapio Ala-Nissila, [Influence of Thermostatting on Nonequilibrium Molecular Dynamics Simulations of Heat Conduction in Solids](https://doi.org/10.1063/1.5132543), J. Chem. Phys. **151**, 234105 (2019).\n",
    "- [Lindsay 2010] L. Lindsay and D.A. Broido, [Optimized Tersoff and Brenner emperical potential parameters for lattice dynamics and phonon thermal transport in carbon nanotubes and graphene](https://doi.org/10.1103/PhysRevB.39.5566), Phys. Rev. B, **81**, 205441 (2010).\n",
    "- [Tersoff 1989] J. Tersoff, [Modeling solid-state chemistry: Interatomic potentials for multicomponent systems](https://doi.org/10.1103/PhysRevB.39.5566), Phys. Rev. B 39, 5566(R) (1989)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
